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context-engineering

MCP serverGitHubActivePython

Context Engineering: Build Consistent, Accurate, Predictable AI Systems

Description provenance: Original source

Open canonical source

Measured: Oct 20, 2026 · 69 observations

Domains & Uses

Domains
Agents, skills and MCP
Uses
Agent skills, Retrieval-augmented generation (RAG)

Check at the source

Compatibility and prerequisites must be checked in the official documentation.

https://github.com/bonigarcia/context-engineering

Classifications

Nature
Tool

Measurement history

Comparable readings are grouped by signal and unit.

Stars

170stars · Oct 20, 2026

+15 (+9.7 %)since Sep 22, 2026

Sep 22, 2026 : 155 starsSep 23, 2026 : 155 starsSep 24, 2026 : 155 starsSep 25, 2026 : 155 starsSep 26, 2026 : 156 starsSep 27, 2026 : 156 starsSep 28, 2026 : 156 starsSep 29, 2026 : 156 starsSep 30, 2026 : 157 starsOct 1, 2026 : 159 starsOct 2, 2026 : 159 starsOct 3, 2026 : 159 starsOct 4, 2026 : 159 starsOct 5, 2026 : 160 starsOct 6, 2026 : 160 starsOct 7, 2026 : 162 starsOct 8, 2026 : 163 starsOct 9, 2026 : 164 starsOct 10, 2026 : 164 starsOct 11, 2026 : 164 starsOct 12, 2026 : 165 starsOct 13, 2026 : 165 starsOct 14, 2026 : 167 starsOct 15, 2026 : 168 starsOct 16, 2026 : 168 starsOct 17, 2026 : 168 starsOct 18, 2026 : 169 starsOct 19, 2026 : 169 starsOct 20, 2026 : 170 stars
Exact values · 29 readings
MeasuredstarsChange
170+1
1690
169+1
1680
1680
168+1
167+2
1650
165+1
1640
1640
164+1
163+1
162+2
1600
160+1
1590
1590
1590
159+2
157+1
1560
1560
1560
156+1
1550
1550
1550
155·